Displaying a previously created Matplotlib figure in a widget
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 35/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- jupyter-notebook, matplotlib, python
- Domain
- data-visualization, frontend
Research direction
Download and run the linked Output Example Notebook to reproduce the behavior with the previously created figure, Output widget, and HBox. Start by tracing how the displayed figure and its canvas are handled, then verify that the figure retains ipympl interactivity in the HBox and that displaying fig1 no longer raises the reported NoneType error.
Written by the indexing model from the issue text.
Description
I'm trying to find a way to take a figure previously created, and show it inside a widget, without losing interactivity.
Here's a short version of my approach (which may not be the right one):
fig = plt.figure() # previously created figure
out = widgets.Output()
with out:
display(fig)
# other things happening
display(widgets.HBox([fig.canvas, some_other_fig]))
If I first create a figure in the notebook outside of an Output widget, and then wish to include it later inside something like an HBox next to a second figure, I seem to lose interactivity with the figure (including the nice ipympl zoom interface).
Here is a nbviewer view of a MWE notebook I created, download it top right on the window. It's best if one downloads it and runs it since the first figure appears buggy in the nbviewer.
Additionally, and I might create a new issue for this - if I call fig1 at the end of the notebook, I get an unexpected error. Here I'd expect the regular figure to be shown. The error is AttributeError: 'NoneType' object has no attribute '_send_event'.
- Dominant language
- Jupyter Notebook
- Stars
- 1.7k
- Forks
- 234
- PR merge metrics
- No merged PRs in 30d
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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